Overview

Dataset statistics

 AB Control GroupAB Test Group
Number of variables1818
Number of observations1815219714
Missing cells00
Missing cells (%)0.0%0.0%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory3.1 MiB3.4 MiB
Average record size in memory181.1 B178.8 B

Variable types

 AB Control GroupAB Test Group
Numeric77
Categorical1111

Alerts

AB Control GroupAB Test Group
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique
Unnamed: 0 has unique values Unnamed: 0 has unique values Unique

Reproduction

 AB Control GroupAB Test Group
Analysis started2023-04-12 15:14:51.1538942023-04-12 15:15:01.558087
Analysis finished2023-04-12 15:15:01.5523202023-04-12 15:15:12.525959
Duration10.4 seconds10.97 seconds
Software versionpandas-profiling vv3.5.0pandas-profiling vv3.5.0
Download configurationconfig.jsonconfig.json

Variables

Unnamed: 0
Real number (ℝ)

 AB Control GroupAB Test Group
Distinct1815219714
Distinct (%)100.0%100.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean25069.43924976.086
 AB Control GroupAB Test Group
Minimum61
Maximum4999849997
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2023-04-12T16:15:12.854862image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

 AB Control GroupAB Test Group
Minimum61
5-th percentile2520.752529.25
Q112560.7512446
median25044.525010.5
Q337692.2537520.5
95-th percentile47539.4547523.4
Maximum4999849997
Range4999249996
Interquartile range (IQR)25131.525074.5

Descriptive statistics

 AB Control GroupAB Test Group
Standard deviation14457.94914458.201
Coefficient of variation (CV)0.576716090.57888175
Kurtosis-1.2094048-1.2011153
Mean25069.43924976.086
Median Absolute Deviation (MAD)1257012532.5
Skewness-0.000165630590.0028708418
Sum4.5506046 × 1084.9237856 × 108
Variance2.0903229 × 1082.0903956 × 108
MonotonicityStrictly increasingStrictly increasing
2023-04-12T16:15:13.129616image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 1
 
< 0.1%
33503 1
 
< 0.1%
33522 1
 
< 0.1%
33520 1
 
< 0.1%
33519 1
 
< 0.1%
33508 1
 
< 0.1%
33506 1
 
< 0.1%
33504 1
 
< 0.1%
33497 1
 
< 0.1%
33533 1
 
< 0.1%
Other values (18142) 18142
99.9%
ValueCountFrequency (%)
1 1
 
< 0.1%
33247 1
 
< 0.1%
33269 1
 
< 0.1%
33256 1
 
< 0.1%
33255 1
 
< 0.1%
33254 1
 
< 0.1%
33253 1
 
< 0.1%
33250 1
 
< 0.1%
33249 1
 
< 0.1%
33244 1
 
< 0.1%
Other values (19704) 19704
99.9%
ValueCountFrequency (%)
6 1
< 0.1%
7 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
20 1
< 0.1%
21 1
< 0.1%
22 1
< 0.1%
25 1
< 0.1%
30 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
33 1
< 0.1%
35 1
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
33 1
< 0.1%
35 1
< 0.1%
ValueCountFrequency (%)
6 1
< 0.1%
7 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
20 1
< 0.1%
21 1
< 0.1%
22 1
< 0.1%
25 1
< 0.1%
30 1
< 0.1%

date_crawled
Categorical

 AB Control GroupAB Test Group
Distinct56015950
Distinct (%)30.9%30.2%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2016-03-25 16:56
 
11
2016-03-27 19:46
 
11
2016-03-08 11:51
 
11
2016-03-12 15:52
 
11
2016-03-31 16:48
 
11
Other values (5596)
18097 
2016-03-30 19:50
 
13
2016-03-05 19:49
 
11
2016-03-16 11:45
 
11
2016-03-31 20:48
 
11
2016-03-25 13:55
 
11
Other values (5945)
19657 

Length

 AB Control GroupAB Test Group
Max length1616
Median length1616
Mean length15.86491815.872629
Min length1515

Characters and Unicode

 AB Control GroupAB Test Group
Total characters287980312913
Distinct characters1313
Distinct categories44 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique12411283 ?
Unique (%)6.8%6.5%

Sample

 AB Control GroupAB Test Group
1st row2016-03-23 19:432016-04-02 14:51
2nd row2016-03-12 13:462016-03-19 18:36
3rd row2016-03-22 14:502016-03-09 20:59
4th row2016-04-04 11:502016-03-26 15:55
5th row2016-03-22 11:592016-03-29 14:47

Common Values

ValueCountFrequency (%)
2016-03-25 16:56 11
 
0.1%
2016-03-27 19:46 11
 
0.1%
2016-03-08 11:51 11
 
0.1%
2016-03-12 15:52 11
 
0.1%
2016-03-31 16:48 11
 
0.1%
2016-03-31 19:55 10
 
0.1%
2016-03-07 19:41 10
 
0.1%
2016-03-12 15:43 10
 
0.1%
2016-04-05 0:37 10
 
0.1%
2016-04-04 13:52 10
 
0.1%
Other values (5591) 18047
99.4%
ValueCountFrequency (%)
2016-03-30 19:50 13
 
0.1%
2016-03-05 19:49 11
 
0.1%
2016-03-16 11:45 11
 
0.1%
2016-03-31 20:48 11
 
0.1%
2016-03-25 13:55 11
 
0.1%
2016-04-02 23:51 11
 
0.1%
2016-04-01 20:54 11
 
0.1%
2016-03-12 17:43 10
 
0.1%
2016-03-12 12:45 10
 
0.1%
2016-03-19 18:38 10
 
0.1%
Other values (5940) 19605
99.4%

Length

2023-04-12T16:15:13.401273image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

AB Test Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
2016-03-15 975
 
2.7%
2016-03-22 876
 
2.4%
2016-03-31 817
 
2.3%
2016-03-21 803
 
2.2%
2016-04-03 796
 
2.2%
2016-03-26 767
 
2.1%
2016-03-28 747
 
2.1%
2016-03-07 724
 
2.0%
2016-03-14 715
 
2.0%
2016-03-29 679
 
1.9%
Other values (679) 28405
78.2%
ValueCountFrequency (%)
2016-03-20 1082
 
2.7%
2016-03-09 923
 
2.3%
2016-04-04 881
 
2.2%
2016-04-01 852
 
2.2%
2016-03-25 831
 
2.1%
2016-03-19 819
 
2.1%
2016-03-23 807
 
2.0%
2016-03-11 793
 
2.0%
2016-03-12 777
 
2.0%
2016-04-02 764
 
1.9%
Other values (734) 30899
78.4%

Most occurring characters

ValueCountFrequency (%)
0 47696
16.6%
1 40973
14.2%
- 36304
12.6%
2 34012
11.8%
3 24987
8.7%
6 24152
8.4%
18152
 
6.3%
: 18152
 
6.3%
5 13922
 
4.8%
4 12656
 
4.4%
Other values (3) 16974
 
5.9%
ValueCountFrequency (%)
0 53098
17.0%
1 45344
14.5%
- 39428
12.6%
2 37150
11.9%
3 26106
8.3%
6 25522
8.2%
19714
 
6.3%
: 19714
 
6.3%
4 14684
 
4.7%
5 14084
 
4.5%
Other values (3) 18069
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 215372
74.8%
Dash Punctuation 36304
 
12.6%
Space Separator 18152
 
6.3%
Other Punctuation 18152
 
6.3%
ValueCountFrequency (%)
Decimal Number 234057
74.8%
Dash Punctuation 39428
 
12.6%
Space Separator 19714
 
6.3%
Other Punctuation 19714
 
6.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47696
22.1%
1 40973
19.0%
2 34012
15.8%
3 24987
11.6%
6 24152
11.2%
5 13922
 
6.5%
4 12656
 
5.9%
7 6098
 
2.8%
8 5543
 
2.6%
9 5333
 
2.5%
ValueCountFrequency (%)
0 53098
22.7%
1 45344
19.4%
2 37150
15.9%
3 26106
11.2%
6 25522
10.9%
4 14684
 
6.3%
5 14084
 
6.0%
7 6216
 
2.7%
8 5998
 
2.6%
9 5855
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 36304
100.0%
ValueCountFrequency (%)
- 39428
100.0%
Space Separator
ValueCountFrequency (%)
18152
100.0%
ValueCountFrequency (%)
19714
100.0%
Other Punctuation
ValueCountFrequency (%)
: 18152
100.0%
ValueCountFrequency (%)
: 19714
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 287980
100.0%
ValueCountFrequency (%)
Common 312913
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 47696
16.6%
1 40973
14.2%
- 36304
12.6%
2 34012
11.8%
3 24987
8.7%
6 24152
8.4%
18152
 
6.3%
: 18152
 
6.3%
5 13922
 
4.8%
4 12656
 
4.4%
Other values (3) 16974
 
5.9%
ValueCountFrequency (%)
0 53098
17.0%
1 45344
14.5%
- 39428
12.6%
2 37150
11.9%
3 26106
8.3%
6 25522
8.2%
19714
 
6.3%
: 19714
 
6.3%
4 14684
 
4.7%
5 14084
 
4.5%
Other values (3) 18069
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 287980
100.0%
ValueCountFrequency (%)
ASCII 312913
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 47696
16.6%
1 40973
14.2%
- 36304
12.6%
2 34012
11.8%
3 24987
8.7%
6 24152
8.4%
18152
 
6.3%
: 18152
 
6.3%
5 13922
 
4.8%
4 12656
 
4.4%
Other values (3) 16974
 
5.9%
ValueCountFrequency (%)
0 53098
17.0%
1 45344
14.5%
- 39428
12.6%
2 37150
11.9%
3 26106
8.3%
6 25522
8.2%
19714
 
6.3%
: 19714
 
6.3%
4 14684
 
4.7%
5 14084
 
4.5%
Other values (3) 18069
 
5.8%

car_name
Categorical

 AB Control GroupAB Test Group
Distinct1469515745
Distinct (%)81.0%79.9%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
BMW_318i
 
51
Volkswagen_Golf_1.4
 
37
BMW_320i
 
34
BMW_316i
 
29
Volkswagen_Polo
 
27
Other values (14690)
17974 
Volkswagen_Golf_1.4
 
53
BMW_318i
 
41
BMW_320i
 
37
BMW_116i
 
35
Volkswagen_Polo_1.2
 
35
Other values (15740)
19513 

Length

 AB Control GroupAB Test Group
Max length6867
Median length4847
Mean length32.75115732.699959
Min length66

Characters and Unicode

 AB Control GroupAB Test Group
Total characters594499644647
Distinct characters101105
Distinct categories914 ?
Distinct scripts22 ?
Distinct blocks22 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique1331914202 ?
Unique (%)73.4%72.0%

Sample

 AB Control GroupAB Test Group
1st rowFord_Mondeo_V6_170_PSAstra_G_Cabrio_Turbo_235_PS
2nd rowBMW_320d_DPF_TouringFiat_Grande_Punto_1.2_8V__MIT_2_JAHREN_GARANTIE
3rd rowHyundai_i30_1.6_CRDi_Edition_20Volvo_XC60_D5_AWD_Aut.
4th rowMercedes_Benz_E_320_T_CDI_Avantgarde__VollausstattungKombi_Technisch_super_in_Schuss
5th rowBMW_120d_DPF_Bus._Navi__Harman&Kardon__SchiebedachAudi_A4_1.9_TDI_quattro_Delphingrau

Common Values

ValueCountFrequency (%)
BMW_318i 51
 
0.3%
Volkswagen_Golf_1.4 37
 
0.2%
BMW_320i 34
 
0.2%
BMW_316i 29
 
0.2%
Volkswagen_Polo 27
 
0.1%
Opel_Corsa_1.0_12V 26
 
0.1%
Opel_Corsa 25
 
0.1%
Volkswagen_Golf_1.6 24
 
0.1%
MINI_Mini_One 24
 
0.1%
Audi_A6_Avant_2.5_TDI 23
 
0.1%
Other values (14685) 17852
98.3%
ValueCountFrequency (%)
Volkswagen_Golf_1.4 53
 
0.3%
BMW_318i 41
 
0.2%
BMW_320i 37
 
0.2%
BMW_116i 35
 
0.2%
Volkswagen_Polo_1.2 35
 
0.2%
Volkswagen_Polo 34
 
0.2%
BMW_316i 32
 
0.2%
Opel_Corsa 30
 
0.2%
Volkswagen_Golf 30
 
0.2%
Volkswagen_Golf_1.6 27
 
0.1%
Other values (15735) 19360
98.2%

Length

2023-04-12T16:15:13.785637image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

AB Test Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
bmw_318i 51
 
0.3%
volkswagen_golf_1.4 37
 
0.2%
bmw_320i 34
 
0.2%
bmw_316i 30
 
0.2%
opel_corsa 29
 
0.2%
ford_fiesta 27
 
0.1%
volkswagen_polo 27
 
0.1%
opel_corsa_1.0_12v 27
 
0.1%
volkswagen_golf_1.6 24
 
0.1%
mini_mini_one 24
 
0.1%
Other values (14496) 17842
98.3%
ValueCountFrequency (%)
volkswagen_golf_1.4 53
 
0.3%
bmw_318i 41
 
0.2%
bmw_320i 37
 
0.2%
bmw_116i 36
 
0.2%
volkswagen_polo_1.2 35
 
0.2%
volkswagen_polo 34
 
0.2%
opel_corsa 33
 
0.2%
bmw_316i 32
 
0.2%
volkswagen_golf 30
 
0.2%
ford_fiesta 28
 
0.1%
Other values (15500) 19355
98.2%

Most occurring characters

ValueCountFrequency (%)
_ 93532
 
15.7%
e 38504
 
6.5%
a 29288
 
4.9%
o 25800
 
4.3%
i 24515
 
4.1%
t 22492
 
3.8%
n 21810
 
3.7%
r 21399
 
3.6%
l 17125
 
2.9%
u 15619
 
2.6%
Other values (91) 284415
47.8%
ValueCountFrequency (%)
_ 101485
 
15.7%
e 41588
 
6.5%
a 31812
 
4.9%
o 28242
 
4.4%
i 27092
 
4.2%
t 24884
 
3.9%
n 23846
 
3.7%
r 23089
 
3.6%
l 18598
 
2.9%
u 16993
 
2.6%
Other values (95) 307018
47.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 309864
52.1%
Uppercase Letter 120884
 
20.3%
Connector Punctuation 93532
 
15.7%
Decimal Number 54408
 
9.2%
Other Punctuation 15240
 
2.6%
Math Symbol 509
 
0.1%
Control 50
 
< 0.1%
Modifier Symbol 10
 
< 0.1%
Other Number 2
 
< 0.1%
ValueCountFrequency (%)
Lowercase Letter 337529
52.4%
Uppercase Letter 129659
 
20.1%
Connector Punctuation 101485
 
15.7%
Decimal Number 59214
 
9.2%
Other Punctuation 16181
 
2.5%
Math Symbol 482
 
0.1%
Control 62
 
< 0.1%
Modifier Symbol 27
 
< 0.1%
Other Number 3
 
< 0.1%
Other Symbol 1
 
< 0.1%
Other values (4) 4
 
< 0.1%

Most frequent character per category

Connector Punctuation
ValueCountFrequency (%)
_ 93532
100.0%
ValueCountFrequency (%)
_ 101485
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 38504
12.4%
a 29288
 
9.5%
o 25800
 
8.3%
i 24515
 
7.9%
t 22492
 
7.3%
n 21810
 
7.0%
r 21399
 
6.9%
l 17125
 
5.5%
u 15619
 
5.0%
s 15385
 
5.0%
Other values (22) 77927
25.1%
ValueCountFrequency (%)
e 41588
12.3%
a 31812
 
9.4%
o 28242
 
8.4%
i 27092
 
8.0%
t 24884
 
7.4%
n 23846
 
7.1%
r 23089
 
6.8%
l 18598
 
5.5%
u 16993
 
5.0%
s 16561
 
4.9%
Other values (21) 84824
25.1%
Decimal Number
ValueCountFrequency (%)
1 11936
21.9%
0 10402
19.1%
2 8869
16.3%
6 4721
 
8.7%
3 4624
 
8.5%
4 3940
 
7.2%
5 3217
 
5.9%
8 2755
 
5.1%
7 2209
 
4.1%
9 1735
 
3.2%
ValueCountFrequency (%)
1 12995
21.9%
0 11329
19.1%
2 9666
16.3%
6 5087
 
8.6%
3 4932
 
8.3%
4 4356
 
7.4%
5 3571
 
6.0%
8 2993
 
5.1%
7 2301
 
3.9%
9 1984
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
T 11223
 
9.3%
A 9653
 
8.0%
S 8334
 
6.9%
V 8320
 
6.9%
C 8249
 
6.8%
M 7285
 
6.0%
D 7126
 
5.9%
I 6363
 
5.3%
P 5961
 
4.9%
B 5479
 
4.5%
Other values (22) 42891
35.5%
ValueCountFrequency (%)
T 11863
 
9.1%
A 10482
 
8.1%
S 8980
 
6.9%
V 8939
 
6.9%
C 8744
 
6.7%
M 7967
 
6.1%
D 7753
 
6.0%
I 6852
 
5.3%
P 6462
 
5.0%
B 6078
 
4.7%
Other values (20) 45539
35.1%
Other Punctuation
ValueCountFrequency (%)
. 10478
68.8%
/ 1960
 
12.9%
! 1565
 
10.3%
* 653
 
4.3%
" 239
 
1.6%
& 169
 
1.1%
? 67
 
0.4%
: 53
 
0.3%
; 37
 
0.2%
# 8
 
0.1%
Other values (4) 11
 
0.1%
ValueCountFrequency (%)
. 11377
70.3%
/ 1940
 
12.0%
! 1547
 
9.6%
* 690
 
4.3%
" 273
 
1.7%
& 194
 
1.2%
? 59
 
0.4%
: 45
 
0.3%
; 32
 
0.2%
# 13
 
0.1%
Other values (3) 11
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 376
73.9%
| 66
 
13.0%
~ 35
 
6.9%
> 16
 
3.1%
< 12
 
2.4%
= 4
 
0.8%
ValueCountFrequency (%)
+ 376
78.0%
| 56
 
11.6%
~ 37
 
7.7%
× 6
 
1.2%
> 4
 
0.8%
< 2
 
0.4%
= 1
 
0.2%
Control
ValueCountFrequency (%)
€ 38
76.0%
– 5
 
10.0%
“ 4
 
8.0%
„ 3
 
6.0%
ValueCountFrequency (%)
€ 43
69.4%
• 11
 
17.7%
– 7
 
11.3%
Š 1
 
1.6%
Modifier Symbol
ValueCountFrequency (%)
´ 10
100.0%
ValueCountFrequency (%)
´ 20
74.1%
^ 5
 
18.5%
` 2
 
7.4%
Other Number
ValueCountFrequency (%)
³ 2
100.0%
ValueCountFrequency (%)
³ 3
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%
Final Punctuation
ValueCountFrequency (%)
» 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 1
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 430748
72.5%
Common 163751
 
27.5%
ValueCountFrequency (%)
Latin 467188
72.5%
Common 177459
 
27.5%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 93532
57.1%
1 11936
 
7.3%
. 10478
 
6.4%
0 10402
 
6.4%
2 8869
 
5.4%
6 4721
 
2.9%
3 4624
 
2.8%
4 3940
 
2.4%
5 3217
 
2.0%
8 2755
 
1.7%
Other values (27) 9277
 
5.7%
ValueCountFrequency (%)
_ 101485
57.2%
1 12995
 
7.3%
. 11377
 
6.4%
0 11329
 
6.4%
2 9666
 
5.4%
6 5087
 
2.9%
3 4932
 
2.8%
4 4356
 
2.5%
5 3571
 
2.0%
8 2993
 
1.7%
Other values (34) 9668
 
5.4%
Latin
ValueCountFrequency (%)
e 38504
 
8.9%
a 29288
 
6.8%
o 25800
 
6.0%
i 24515
 
5.7%
t 22492
 
5.2%
n 21810
 
5.1%
r 21399
 
5.0%
l 17125
 
4.0%
u 15619
 
3.6%
s 15385
 
3.6%
Other values (54) 198811
46.2%
ValueCountFrequency (%)
e 41588
 
8.9%
a 31812
 
6.8%
o 28242
 
6.0%
i 27092
 
5.8%
t 24884
 
5.3%
n 23846
 
5.1%
r 23089
 
4.9%
l 18598
 
4.0%
u 16993
 
3.6%
s 16561
 
3.5%
Other values (51) 214483
45.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 592856
99.7%
None 1643
 
0.3%
ValueCountFrequency (%)
ASCII 642911
99.7%
None 1736
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 93532
 
15.8%
e 38504
 
6.5%
a 29288
 
4.9%
o 25800
 
4.4%
i 24515
 
4.1%
t 22492
 
3.8%
n 21810
 
3.7%
r 21399
 
3.6%
l 17125
 
2.9%
u 15619
 
2.6%
Other values (72) 282772
47.7%
ValueCountFrequency (%)
_ 101485
 
15.8%
e 41588
 
6.5%
a 31812
 
4.9%
o 28242
 
4.4%
i 27092
 
4.2%
t 24884
 
3.9%
n 23846
 
3.7%
r 23089
 
3.6%
l 18598
 
2.9%
u 16993
 
2.6%
Other values (75) 305282
47.5%
None
ValueCountFrequency (%)
Ü 1335
81.3%
ë 173
 
10.5%
€ 38
 
2.3%
é 33
 
2.0%
Ä 15
 
0.9%
´ 10
 
0.6%
Ö 8
 
0.5%
– 5
 
0.3%
“ 4
 
0.2%
è 3
 
0.2%
Other values (9) 19
 
1.2%
ValueCountFrequency (%)
Ü 1381
79.6%
ë 179
 
10.3%
é 48
 
2.8%
€ 43
 
2.5%
´ 20
 
1.2%
Ä 15
 
0.9%
Ö 13
 
0.7%
• 11
 
0.6%
– 7
 
0.4%
× 6
 
0.3%
Other values (10) 13
 
0.7%

price_EUR
Real number (ℝ)

 AB Control GroupAB Test Group
Distinct15591568
Distinct (%)8.6%8.0%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean6874.7766804.5481
 AB Control GroupAB Test Group
Minimum500500
Maximum820000600000
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2023-04-12T16:15:14.156176image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

 AB Control GroupAB Test Group
Minimum500500
5-th percentile700700
Q117501700
median39503950
Q385008599
95-th percentile21763.521500
Maximum820000600000
Range819500599500
Interquartile range (IQR)67506899

Descriptive statistics

 AB Control GroupAB Test Group
Standard deviation12661.81710561.905
Coefficient of variation (CV)1.84177891.5521832
Kurtosis1550.2578811.57384
Mean6874.7766804.5481
Median Absolute Deviation (MAD)27002700
Skewness29.53994818.643861
Sum1.2479093 × 1081.3414486 × 108
Variance1.6032161 × 1081.1155384 × 108
MonotonicityNot monotonicNot monotonic
2023-04-12T16:15:14.418673image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500 260
 
1.4%
1500 259
 
1.4%
1200 231
 
1.3%
2500 225
 
1.2%
1000 219
 
1.2%
3500 201
 
1.1%
800 188
 
1.0%
2000 184
 
1.0%
650 168
 
0.9%
4500 166
 
0.9%
Other values (1549) 16051
88.4%
ValueCountFrequency (%)
1500 270
 
1.4%
500 269
 
1.4%
2500 251
 
1.3%
1200 241
 
1.2%
1000 208
 
1.1%
800 197
 
1.0%
3500 182
 
0.9%
2000 179
 
0.9%
999 176
 
0.9%
600 172
 
0.9%
Other values (1558) 17569
89.1%
ValueCountFrequency (%)
500 260
1.4%
501 1
 
< 0.1%
510 1
 
< 0.1%
520 1
 
< 0.1%
530 2
 
< 0.1%
540 1
 
< 0.1%
549 7
 
< 0.1%
550 125
0.7%
555 8
 
< 0.1%
570 1
 
< 0.1%
ValueCountFrequency (%)
500 269
1.4%
520 1
 
< 0.1%
525 1
 
< 0.1%
530 2
 
< 0.1%
540 1
 
< 0.1%
545 1
 
< 0.1%
549 7
 
< 0.1%
550 101
 
0.5%
555 14
 
0.1%
560 5
 
< 0.1%
ValueCountFrequency (%)
500 269
1.5%
520 1
 
< 0.1%
525 1
 
< 0.1%
530 2
 
< 0.1%
540 1
 
< 0.1%
545 1
 
< 0.1%
549 7
 
< 0.1%
550 101
 
0.6%
555 14
 
0.1%
560 5
 
< 0.1%
ValueCountFrequency (%)
500 260
1.3%
501 1
 
< 0.1%
510 1
 
< 0.1%
520 1
 
< 0.1%
530 2
 
< 0.1%
540 1
 
< 0.1%
549 7
 
< 0.1%
550 125
0.6%
555 8
 
< 0.1%
570 1
 
< 0.1%

ab_test
Categorical

 AB Control GroupAB Test Group
Distinct11
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
control
18152 
test
19714 

Length

 AB Control GroupAB Test Group
Max length74
Median length74
Mean length74
Min length74

Characters and Unicode

 AB Control GroupAB Test Group
Total characters12706478856
Distinct characters63
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique00 ?
Unique (%)0.0%0.0%

Sample

 AB Control GroupAB Test Group
1st rowcontroltest
2nd rowcontroltest
3rd rowcontroltest
4th rowcontroltest
5th rowcontroltest

Common Values

ValueCountFrequency (%)
control 18152
100.0%
ValueCountFrequency (%)
test 19714
100.0%

Length

2023-04-12T16:15:14.639372image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group

2023-04-12T16:15:14.796574image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:14.906391image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
control 18152
100.0%
ValueCountFrequency (%)
test 19714
100.0%

Most occurring characters

ValueCountFrequency (%)
o 36304
28.6%
c 18152
14.3%
n 18152
14.3%
t 18152
14.3%
r 18152
14.3%
l 18152
14.3%
ValueCountFrequency (%)
t 39428
50.0%
e 19714
25.0%
s 19714
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 127064
100.0%
ValueCountFrequency (%)
Lowercase Letter 78856
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 36304
28.6%
c 18152
14.3%
n 18152
14.3%
t 18152
14.3%
r 18152
14.3%
l 18152
14.3%
ValueCountFrequency (%)
t 39428
50.0%
e 19714
25.0%
s 19714
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 127064
100.0%
ValueCountFrequency (%)
Latin 78856
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 36304
28.6%
c 18152
14.3%
n 18152
14.3%
t 18152
14.3%
r 18152
14.3%
l 18152
14.3%
ValueCountFrequency (%)
t 39428
50.0%
e 19714
25.0%
s 19714
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127064
100.0%
ValueCountFrequency (%)
ASCII 78856
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 36304
28.6%
c 18152
14.3%
n 18152
14.3%
t 18152
14.3%
r 18152
14.3%
l 18152
14.3%
ValueCountFrequency (%)
t 39428
50.0%
e 19714
25.0%
s 19714
25.0%

vehicle_type
Categorical

 AB Control GroupAB Test Group
Distinct99
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
limousine
5234 
kleinwagen
3813 
kombi
3634 
bus
1688 
cabrio
1342 
Other values (4)
2441 
limousine
5812 
kleinwagen
4164 
kombi
3981 
bus
1811 
cabrio
1369 
Other values (4)
2577 

Length

 AB Control GroupAB Test Group
Max length1010
Median length99
Mean length7.051847.0771026
Min length33

Characters and Unicode

 AB Control GroupAB Test Group
Total characters128005139518
Distinct characters1919
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique00 ?
Unique (%)0.0%0.0%

Sample

 AB Control GroupAB Test Group
1st rowlimousinecabrio
2nd rowkombikleinwagen
3rd rowlimousinesuv
4th rowkombikombi
5th rowlimousinelimousine

Common Values

ValueCountFrequency (%)
limousine 5234
28.8%
kleinwagen 3813
21.0%
kombi 3634
20.0%
bus 1688
 
9.3%
cabrio 1342
 
7.4%
coupe 1074
 
5.9%
suv 830
 
4.6%
Unknown 401
 
2.2%
andere 136
 
0.7%
ValueCountFrequency (%)
limousine 5812
29.5%
kleinwagen 4164
21.1%
kombi 3981
20.2%
bus 1811
 
9.2%
cabrio 1369
 
6.9%
coupe 1066
 
5.4%
suv 932
 
4.7%
Unknown 418
 
2.1%
andere 161
 
0.8%

Length

2023-04-12T16:15:15.047312image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group

2023-04-12T16:15:15.227615image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:15.418576image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
limousine 5234
28.8%
kleinwagen 3813
21.0%
kombi 3634
20.0%
bus 1688
 
9.3%
cabrio 1342
 
7.4%
coupe 1074
 
5.9%
suv 830
 
4.6%
unknown 401
 
2.2%
andere 136
 
0.7%
ValueCountFrequency (%)
limousine 5812
29.5%
kleinwagen 4164
21.1%
kombi 3981
20.2%
bus 1811
 
9.2%
cabrio 1369
 
6.9%
coupe 1066
 
5.4%
suv 932
 
4.7%
unknown 418
 
2.1%
andere 161
 
0.8%

Most occurring characters

ValueCountFrequency (%)
i 19257
15.0%
e 14206
11.1%
n 14199
11.1%
o 11685
9.1%
l 9047
7.1%
m 8868
6.9%
u 8826
6.9%
k 7848
 
6.1%
s 7752
 
6.1%
b 6664
 
5.2%
Other values (9) 19653
15.4%
ValueCountFrequency (%)
i 21138
15.2%
n 15555
11.1%
e 15528
11.1%
o 12646
9.1%
l 9976
7.2%
m 9793
7.0%
u 9621
6.9%
k 8563
6.1%
s 8555
6.1%
b 7161
 
5.1%
Other values (9) 20982
15.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 127604
99.7%
Uppercase Letter 401
 
0.3%
ValueCountFrequency (%)
Lowercase Letter 139100
99.7%
Uppercase Letter 418
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 19257
15.1%
e 14206
11.1%
n 14199
11.1%
o 11685
9.2%
l 9047
7.1%
m 8868
6.9%
u 8826
6.9%
k 7848
6.2%
s 7752
6.1%
b 6664
 
5.2%
Other values (8) 19252
15.1%
ValueCountFrequency (%)
i 21138
15.2%
n 15555
11.2%
e 15528
11.2%
o 12646
9.1%
l 9976
7.2%
m 9793
7.0%
u 9621
6.9%
k 8563
6.2%
s 8555
6.2%
b 7161
 
5.1%
Other values (8) 20564
14.8%
Uppercase Letter
ValueCountFrequency (%)
U 401
100.0%
ValueCountFrequency (%)
U 418
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 128005
100.0%
ValueCountFrequency (%)
Latin 139518
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 19257
15.0%
e 14206
11.1%
n 14199
11.1%
o 11685
9.1%
l 9047
7.1%
m 8868
6.9%
u 8826
6.9%
k 7848
 
6.1%
s 7752
 
6.1%
b 6664
 
5.2%
Other values (9) 19653
15.4%
ValueCountFrequency (%)
i 21138
15.2%
n 15555
11.1%
e 15528
11.1%
o 12646
9.1%
l 9976
7.2%
m 9793
7.0%
u 9621
6.9%
k 8563
6.1%
s 8555
6.1%
b 7161
 
5.1%
Other values (9) 20982
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128005
100.0%
ValueCountFrequency (%)
ASCII 139518
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 19257
15.0%
e 14206
11.1%
n 14199
11.1%
o 11685
9.1%
l 9047
7.1%
m 8868
6.9%
u 8826
6.9%
k 7848
 
6.1%
s 7752
 
6.1%
b 6664
 
5.2%
Other values (9) 19653
15.4%
ValueCountFrequency (%)
i 21138
15.2%
n 15555
11.1%
e 15528
11.1%
o 12646
9.1%
l 9976
7.2%
m 9793
7.0%
u 9621
6.9%
k 8563
6.1%
s 8555
6.1%
b 7161
 
5.1%
Other values (9) 20982
15.0%

registration_year
Real number (ℝ)

 AB Control GroupAB Test Group
Distinct6667
Distinct (%)0.4%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean2003.55982003.5012
 AB Control GroupAB Test Group
Minimum19291930
Maximum20162016
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2023-04-12T16:15:15.739933image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

 AB Control GroupAB Test Group
Minimum19291930
5-th percentile19941993
Q120002000
median20042004
Q320082008
95-th percentile20132013
Maximum20162016
Range8786
Interquartile range (IQR)88

Descriptive statistics

 AB Control GroupAB Test Group
Standard deviation6.67181286.774354
Coefficient of variation (CV)0.00332997930.0033812577
Kurtosis7.70154227.0794329
Mean2003.55982003.5012
Median Absolute Deviation (MAD)44
Skewness-1.4814918-1.5132514
Sum3636861839497023
Variance44.51308645.891872
MonotonicityNot monotonicNot monotonic
2023-04-12T16:15:15.944030image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2006 1248
 
6.9%
2005 1211
 
6.7%
2003 1158
 
6.4%
2001 1110
 
6.1%
2002 1087
 
6.0%
1999 1077
 
5.9%
2004 1073
 
5.9%
2000 1021
 
5.6%
2007 996
 
5.5%
2008 959
 
5.3%
Other values (56) 7212
39.7%
ValueCountFrequency (%)
2005 1355
 
6.9%
2004 1237
 
6.3%
2006 1213
 
6.2%
1999 1185
 
6.0%
2002 1172
 
5.9%
2007 1156
 
5.9%
2000 1147
 
5.8%
2003 1118
 
5.7%
2001 1114
 
5.7%
2008 1027
 
5.2%
Other values (57) 7990
40.5%
ValueCountFrequency (%)
1929 1
 
< 0.1%
1931 1
 
< 0.1%
1932 1
 
< 0.1%
1938 1
 
< 0.1%
1945 1
 
< 0.1%
1947 1
 
< 0.1%
1950 1
 
< 0.1%
1957 1
 
< 0.1%
1959 2
 
< 0.1%
1960 5
< 0.1%
ValueCountFrequency (%)
1930 1
 
< 0.1%
1935 1
 
< 0.1%
1939 1
 
< 0.1%
1951 2
< 0.1%
1952 1
 
< 0.1%
1954 1
 
< 0.1%
1956 2
< 0.1%
1957 2
< 0.1%
1958 4
< 0.1%
1959 3
< 0.1%
ValueCountFrequency (%)
1930 1
 
< 0.1%
1935 1
 
< 0.1%
1939 1
 
< 0.1%
1951 2
< 0.1%
1952 1
 
< 0.1%
1954 1
 
< 0.1%
1956 2
< 0.1%
1957 2
< 0.1%
1958 4
< 0.1%
1959 3
< 0.1%
ValueCountFrequency (%)
1929 1
 
< 0.1%
1931 1
 
< 0.1%
1932 1
 
< 0.1%
1938 1
 
< 0.1%
1945 1
 
< 0.1%
1947 1
 
< 0.1%
1950 1
 
< 0.1%
1957 1
 
< 0.1%
1959 2
 
< 0.1%
1960 5
< 0.1%

transmission
Categorical

 AB Control GroupAB Test Group
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
manuell
13625 
automatik
4314 
Unknown
 
213
manuell
14856 
automatik
4605 
Unknown
 
253

Length

 AB Control GroupAB Test Group
Max length99
Median length77
Mean length7.47531957.4671807
Min length77

Characters and Unicode

 AB Control GroupAB Test Group
Total characters135692147208
Distinct characters1212
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique00 ?
Unique (%)0.0%0.0%

Sample

 AB Control GroupAB Test Group
1st rowautomatikmanuell
2nd rowmanuellmanuell
3rd rowmanuellautomatik
4th rowautomatikmanuell
5th rowmanuellmanuell

Common Values

ValueCountFrequency (%)
manuell 13625
75.1%
automatik 4314
 
23.8%
Unknown 213
 
1.2%
ValueCountFrequency (%)
manuell 14856
75.4%
automatik 4605
 
23.4%
Unknown 253
 
1.3%

Length

2023-04-12T16:15:16.163351image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group

2023-04-12T16:15:16.336621image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:16.509712image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
manuell 13625
75.1%
automatik 4314
 
23.8%
unknown 213
 
1.2%
ValueCountFrequency (%)
manuell 14856
75.4%
automatik 4605
 
23.4%
unknown 253
 
1.3%

Most occurring characters

ValueCountFrequency (%)
l 27250
20.1%
a 22253
16.4%
m 17939
13.2%
u 17939
13.2%
n 14264
10.5%
e 13625
10.0%
t 8628
 
6.4%
o 4527
 
3.3%
k 4527
 
3.3%
i 4314
 
3.2%
Other values (2) 426
 
0.3%
ValueCountFrequency (%)
l 29712
20.2%
a 24066
16.3%
m 19461
13.2%
u 19461
13.2%
n 15615
10.6%
e 14856
10.1%
t 9210
 
6.3%
o 4858
 
3.3%
k 4858
 
3.3%
i 4605
 
3.1%
Other values (2) 506
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 135479
99.8%
Uppercase Letter 213
 
0.2%
ValueCountFrequency (%)
Lowercase Letter 146955
99.8%
Uppercase Letter 253
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 27250
20.1%
a 22253
16.4%
m 17939
13.2%
u 17939
13.2%
n 14264
10.5%
e 13625
10.1%
t 8628
 
6.4%
o 4527
 
3.3%
k 4527
 
3.3%
i 4314
 
3.2%
ValueCountFrequency (%)
l 29712
20.2%
a 24066
16.4%
m 19461
13.2%
u 19461
13.2%
n 15615
10.6%
e 14856
10.1%
t 9210
 
6.3%
o 4858
 
3.3%
k 4858
 
3.3%
i 4605
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
U 213
100.0%
ValueCountFrequency (%)
U 253
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 135692
100.0%
ValueCountFrequency (%)
Latin 147208
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 27250
20.1%
a 22253
16.4%
m 17939
13.2%
u 17939
13.2%
n 14264
10.5%
e 13625
10.0%
t 8628
 
6.4%
o 4527
 
3.3%
k 4527
 
3.3%
i 4314
 
3.2%
Other values (2) 426
 
0.3%
ValueCountFrequency (%)
l 29712
20.2%
a 24066
16.3%
m 19461
13.2%
u 19461
13.2%
n 15615
10.6%
e 14856
10.1%
t 9210
 
6.3%
o 4858
 
3.3%
k 4858
 
3.3%
i 4605
 
3.1%
Other values (2) 506
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 135692
100.0%
ValueCountFrequency (%)
ASCII 147208
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 27250
20.1%
a 22253
16.4%
m 17939
13.2%
u 17939
13.2%
n 14264
10.5%
e 13625
10.0%
t 8628
 
6.4%
o 4527
 
3.3%
k 4527
 
3.3%
i 4314
 
3.2%
Other values (2) 426
 
0.3%
ValueCountFrequency (%)
l 29712
20.2%
a 24066
16.3%
m 19461
13.2%
u 19461
13.2%
n 15615
10.6%
e 14856
10.1%
t 9210
 
6.3%
o 4858
 
3.3%
k 4858
 
3.3%
i 4605
 
3.1%
Other values (2) 506
 
0.3%

power_ps
Real number (ℝ)

 AB Control GroupAB Test Group
Distinct344331
Distinct (%)1.9%1.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean130.29958129.00457
 AB Control GroupAB Test Group
Minimum13
Maximum13991403
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2023-04-12T16:15:16.714119image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

 AB Control GroupAB Test Group
Minimum13
5-th percentile5858
Q18686
median116116
Q3160155
95-th percentile239239
Maximum13991403
Range13981400
Interquartile range (IQR)7469

Descriptive statistics

 AB Control GroupAB Test Group
Standard deviation65.11562664.181775
Coefficient of variation (CV)0.49973780.49751553
Kurtosis27.3270330.276162
Mean130.29958129.00457
Median Absolute Deviation (MAD)3434
Skewness2.85175382.926974
Sum23651982543196
Variance4240.04484119.3002
MonotonicityNot monotonicNot monotonic
2023-04-12T16:15:16.933864image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75 1155
 
6.4%
150 847
 
4.7%
140 830
 
4.6%
60 748
 
4.1%
116 716
 
3.9%
101 676
 
3.7%
90 653
 
3.6%
170 614
 
3.4%
105 598
 
3.3%
163 386
 
2.1%
Other values (334) 10929
60.2%
ValueCountFrequency (%)
75 1326
 
6.7%
150 929
 
4.7%
140 901
 
4.6%
60 837
 
4.2%
101 797
 
4.0%
116 747
 
3.8%
105 689
 
3.5%
90 678
 
3.4%
170 673
 
3.4%
136 428
 
2.2%
Other values (321) 11709
59.4%
ValueCountFrequency (%)
1 2
 
< 0.1%
4 2
 
< 0.1%
5 6
< 0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
15 1
 
< 0.1%
17 1
 
< 0.1%
18 3
< 0.1%
20 1
 
< 0.1%
23 2
 
< 0.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
4 1
 
< 0.1%
5 2
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
17 1
 
< 0.1%
18 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
4 1
 
< 0.1%
5 2
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
11 2
< 0.1%
14 1
 
< 0.1%
17 1
 
< 0.1%
18 3
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
4 2
 
< 0.1%
5 6
< 0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
15 1
 
< 0.1%
17 1
 
< 0.1%
18 3
< 0.1%
20 1
 
< 0.1%
23 2
 
< 0.1%

model
Categorical

 AB Control GroupAB Test Group
Distinct241241
Distinct (%)1.3%1.2%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
golf
1501 
andere
 
1291
3er
 
1083
Unknown
 
594
a4
 
552
Other values (236)
13131 
golf
1616 
andere
1427 
3er
 
1177
polo
 
635
a4
 
601
Other values (236)
14258 

Length

 AB Control GroupAB Test Group
Max length1818
Median length1111
Mean length5.10053995.10769
Min length22

Characters and Unicode

 AB Control GroupAB Test Group
Total characters92585100693
Distinct characters3838
Distinct categories44 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique66 ?
Unique (%)< 0.1%< 0.1%

Sample

 AB Control GroupAB Test Group
1st rowmondeoastra
2nd row3erandere
3rd rowi_reihexc_reihe
4th rowe_klassemondeo
5th row1era4

Common Values

ValueCountFrequency (%)
golf 1501
 
8.3%
andere 1291
 
7.1%
3er 1083
 
6.0%
Unknown 594
 
3.3%
a4 552
 
3.0%
polo 537
 
3.0%
corsa 531
 
2.9%
passat 510
 
2.8%
astra 494
 
2.7%
5er 472
 
2.6%
Other values (231) 10587
58.3%
ValueCountFrequency (%)
golf 1616
 
8.2%
andere 1427
 
7.2%
3er 1177
 
6.0%
polo 635
 
3.2%
a4 601
 
3.0%
passat 601
 
3.0%
Unknown 595
 
3.0%
corsa 567
 
2.9%
astra 546
 
2.8%
5er 537
 
2.7%
Other values (231) 11412
57.9%

Length

2023-04-12T16:15:17.201668image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

AB Test Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
golf 1501
 
8.3%
andere 1291
 
7.1%
3er 1083
 
6.0%
unknown 594
 
3.3%
a4 552
 
3.0%
polo 537
 
3.0%
corsa 531
 
2.9%
passat 510
 
2.8%
astra 494
 
2.7%
5er 472
 
2.6%
Other values (231) 10587
58.3%
ValueCountFrequency (%)
golf 1616
 
8.2%
andere 1427
 
7.2%
3er 1177
 
6.0%
polo 635
 
3.2%
a4 601
 
3.0%
passat 601
 
3.0%
unknown 595
 
3.0%
corsa 567
 
2.9%
astra 546
 
2.8%
5er 537
 
2.7%
Other values (231) 11412
57.9%

Most occurring characters

ValueCountFrequency (%)
a 11166
12.1%
e 10980
11.9%
r 8422
 
9.1%
o 7683
 
8.3%
s 6814
 
7.4%
n 5222
 
5.6%
l 4541
 
4.9%
t 3949
 
4.3%
i 3698
 
4.0%
c 3236
 
3.5%
Other values (28) 26874
29.0%
ValueCountFrequency (%)
a 12236
12.2%
e 11985
11.9%
r 9254
 
9.2%
o 8533
 
8.5%
s 7332
 
7.3%
n 5595
 
5.6%
l 4956
 
4.9%
t 4293
 
4.3%
i 4013
 
4.0%
c 3445
 
3.4%
Other values (28) 29051
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 84446
91.2%
Decimal Number 5063
 
5.5%
Connector Punctuation 2482
 
2.7%
Uppercase Letter 594
 
0.6%
ValueCountFrequency (%)
Lowercase Letter 91902
91.3%
Decimal Number 5555
 
5.5%
Connector Punctuation 2641
 
2.6%
Uppercase Letter 595
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 11166
13.2%
e 10980
13.0%
r 8422
10.0%
o 7683
9.1%
s 6814
 
8.1%
n 5222
 
6.2%
l 4541
 
5.4%
t 3949
 
4.7%
i 3698
 
4.4%
c 3236
 
3.8%
Other values (16) 18735
22.2%
ValueCountFrequency (%)
a 12236
13.3%
e 11985
13.0%
r 9254
10.1%
o 8533
9.3%
s 7332
 
8.0%
n 5595
 
6.1%
l 4956
 
5.4%
t 4293
 
4.7%
i 4013
 
4.4%
c 3445
 
3.7%
Other values (16) 20260
22.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2482
100.0%
ValueCountFrequency (%)
_ 2641
100.0%
Decimal Number
ValueCountFrequency (%)
3 1667
32.9%
5 738
14.6%
4 675
13.3%
1 532
 
10.5%
6 483
 
9.5%
0 331
 
6.5%
2 302
 
6.0%
7 158
 
3.1%
8 102
 
2.0%
9 75
 
1.5%
ValueCountFrequency (%)
3 1768
31.8%
5 818
14.7%
4 743
13.4%
1 656
 
11.8%
6 522
 
9.4%
0 388
 
7.0%
2 310
 
5.6%
7 156
 
2.8%
8 100
 
1.8%
9 94
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
U 594
100.0%
ValueCountFrequency (%)
U 595
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 85040
91.9%
Common 7545
 
8.1%
ValueCountFrequency (%)
Latin 92497
91.9%
Common 8196
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 11166
13.1%
e 10980
12.9%
r 8422
9.9%
o 7683
 
9.0%
s 6814
 
8.0%
n 5222
 
6.1%
l 4541
 
5.3%
t 3949
 
4.6%
i 3698
 
4.3%
c 3236
 
3.8%
Other values (17) 19329
22.7%
ValueCountFrequency (%)
a 12236
13.2%
e 11985
13.0%
r 9254
10.0%
o 8533
9.2%
s 7332
 
7.9%
n 5595
 
6.0%
l 4956
 
5.4%
t 4293
 
4.6%
i 4013
 
4.3%
c 3445
 
3.7%
Other values (17) 20855
22.5%
Common
ValueCountFrequency (%)
_ 2482
32.9%
3 1667
22.1%
5 738
 
9.8%
4 675
 
8.9%
1 532
 
7.1%
6 483
 
6.4%
0 331
 
4.4%
2 302
 
4.0%
7 158
 
2.1%
8 102
 
1.4%
ValueCountFrequency (%)
_ 2641
32.2%
3 1768
21.6%
5 818
 
10.0%
4 743
 
9.1%
1 656
 
8.0%
6 522
 
6.4%
0 388
 
4.7%
2 310
 
3.8%
7 156
 
1.9%
8 100
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92585
100.0%
ValueCountFrequency (%)
ASCII 100693
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 11166
12.1%
e 10980
11.9%
r 8422
 
9.1%
o 7683
 
8.3%
s 6814
 
7.4%
n 5222
 
5.6%
l 4541
 
4.9%
t 3949
 
4.3%
i 3698
 
4.0%
c 3236
 
3.5%
Other values (28) 26874
29.0%
ValueCountFrequency (%)
a 12236
12.2%
e 11985
11.9%
r 9254
 
9.2%
o 8533
 
8.5%
s 7332
 
7.3%
n 5595
 
5.6%
l 4956
 
4.9%
t 4293
 
4.3%
i 4013
 
4.0%
c 3445
 
3.4%
Other values (28) 29051
28.9%

odometer_km
Real number (ℝ)

 AB Control GroupAB Test Group
Distinct1313
Distinct (%)0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean124434.22124120.17
 AB Control GroupAB Test Group
Minimum50005000
Maximum150000150000
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2023-04-12T16:15:17.483973image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

 AB Control GroupAB Test Group
Minimum50005000
5-th percentile3000040000
Q1100000100000
median150000150000
Q3150000150000
95-th percentile150000150000
Maximum150000150000
Range145000145000
Interquartile range (IQR)5000050000

Descriptive statistics

 AB Control GroupAB Test Group
Standard deviation39761.31239768.559
Coefficient of variation (CV)0.319536790.32040368
Kurtosis0.697778140.66066029
Mean124434.22124120.17
Median Absolute Deviation (MAD)00
Skewness-1.3972352-1.3775739
Sum2.25873 × 1092.446905 × 109
Variance1.5809619 × 1091.5815383 × 109
MonotonicityNot monotonicNot monotonic
2023-04-12T16:15:17.694813image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
150000 11333
62.4%
125000 1971
 
10.9%
100000 820
 
4.5%
90000 679
 
3.7%
80000 587
 
3.2%
70000 533
 
2.9%
60000 487
 
2.7%
50000 419
 
2.3%
40000 394
 
2.2%
30000 362
 
2.0%
Other values (3) 567
 
3.1%
ValueCountFrequency (%)
150000 12180
61.8%
125000 2190
 
11.1%
100000 899
 
4.6%
90000 756
 
3.8%
80000 642
 
3.3%
70000 637
 
3.2%
60000 544
 
2.8%
50000 476
 
2.4%
40000 405
 
2.1%
30000 367
 
1.9%
Other values (3) 618
 
3.1%
ValueCountFrequency (%)
5000 147
 
0.8%
10000 90
 
0.5%
20000 330
1.8%
30000 362
2.0%
40000 394
2.2%
50000 419
2.3%
60000 487
2.7%
70000 533
2.9%
80000 587
3.2%
90000 679
3.7%
ValueCountFrequency (%)
5000 175
 
0.9%
10000 112
 
0.6%
20000 331
1.7%
30000 367
1.9%
40000 405
2.1%
50000 476
2.4%
60000 544
2.8%
70000 637
3.2%
80000 642
3.3%
90000 756
3.8%
ValueCountFrequency (%)
5000 175
 
1.0%
10000 112
 
0.6%
20000 331
1.8%
30000 367
2.0%
40000 405
2.2%
50000 476
2.6%
60000 544
3.0%
70000 637
3.5%
80000 642
3.5%
90000 756
4.2%
ValueCountFrequency (%)
5000 147
 
0.7%
10000 90
 
0.5%
20000 330
1.7%
30000 362
1.8%
40000 394
2.0%
50000 419
2.1%
60000 487
2.5%
70000 533
2.7%
80000 587
3.0%
90000 679
3.4%

registration_month
Real number (ℝ)

 AB Control GroupAB Test Group
Distinct1212
Distinct (%)0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean6.37455936.4173176
 AB Control GroupAB Test Group
Minimum11
Maximum1212
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2023-04-12T16:15:17.876928image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

 AB Control GroupAB Test Group
Minimum11
5-th percentile11
Q144
median66
Q399
95-th percentile1212
Maximum1212
Range1111
Interquartile range (IQR)55

Descriptive statistics

 AB Control GroupAB Test Group
Standard deviation3.34338863.3333668
Coefficient of variation (CV)0.524489380.51943303
Kurtosis-1.1462828-1.1427767
Mean6.37455936.4173176
Median Absolute Deviation (MAD)33
Skewness0.112703060.09005205
Sum115711126511
Variance11.17824811.111334
MonotonicityNot monotonicNot monotonic
2023-04-12T16:15:18.049921image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 1977
10.9%
6 1799
9.9%
5 1730
9.5%
4 1715
9.4%
7 1502
8.3%
10 1490
8.2%
12 1407
7.8%
9 1368
7.5%
11 1337
7.4%
8 1301
7.2%
Other values (2) 2526
13.9%
ValueCountFrequency (%)
3 2121
10.8%
6 1938
9.8%
4 1860
9.4%
5 1844
9.4%
7 1718
8.7%
10 1611
8.2%
9 1522
7.7%
11 1521
7.7%
12 1500
7.6%
8 1425
7.2%
Other values (2) 2654
13.5%
ValueCountFrequency (%)
1 1301
7.2%
2 1225
6.7%
3 1977
10.9%
4 1715
9.4%
5 1730
9.5%
6 1799
9.9%
7 1502
8.3%
8 1301
7.2%
9 1368
7.5%
10 1490
8.2%
ValueCountFrequency (%)
1 1413
7.2%
2 1241
6.3%
3 2121
10.8%
4 1860
9.4%
5 1844
9.4%
6 1938
9.8%
7 1718
8.7%
8 1425
7.2%
9 1522
7.7%
10 1611
8.2%
ValueCountFrequency (%)
1 1413
7.8%
2 1241
6.8%
3 2121
11.7%
4 1860
10.2%
5 1844
10.2%
6 1938
10.7%
7 1718
9.5%
8 1425
7.9%
9 1522
8.4%
10 1611
8.9%
ValueCountFrequency (%)
1 1301
6.6%
2 1225
6.2%
3 1977
10.0%
4 1715
8.7%
5 1730
8.8%
6 1799
9.1%
7 1502
7.6%
8 1301
6.6%
9 1368
6.9%
10 1490
7.6%

fuel_type
Categorical

 AB Control GroupAB Test Group
Distinct88
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
benzin
11212 
diesel
5937 
Unknown
 
642
lpg
 
305
cng
 
29
Other values (3)
 
27
benzin
12244 
diesel
6480 
Unknown
 
643
lpg
 
298
cng
 
24
Other values (3)
 
25

Length

 AB Control GroupAB Test Group
Max length77
Median length66
Mean length5.98022265.9837172
Min length33

Characters and Unicode

 AB Control GroupAB Test Group
Total characters108553117963
Distinct characters2020
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique10 ?
Unique (%)< 0.1%0.0%

Sample

 AB Control GroupAB Test Group
1st rowbenzinUnknown
2nd rowdieselbenzin
3rd rowdieseldiesel
4th rowdieselbenzin
5th rowdieseldiesel

Common Values

ValueCountFrequency (%)
benzin 11212
61.8%
diesel 5937
32.7%
Unknown 642
 
3.5%
lpg 305
 
1.7%
cng 29
 
0.2%
hybrid 19
 
0.1%
andere 7
 
< 0.1%
elektro 1
 
< 0.1%
ValueCountFrequency (%)
benzin 12244
62.1%
diesel 6480
32.9%
Unknown 643
 
3.3%
lpg 298
 
1.5%
cng 24
 
0.1%
hybrid 16
 
0.1%
andere 7
 
< 0.1%
elektro 2
 
< 0.1%

Length

2023-04-12T16:15:18.269765image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group

2023-04-12T16:15:18.597001image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:18.769253image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
benzin 11212
61.8%
diesel 5937
32.7%
unknown 642
 
3.5%
lpg 305
 
1.7%
cng 29
 
0.2%
hybrid 19
 
0.1%
andere 7
 
< 0.1%
elektro 1
 
< 0.1%
ValueCountFrequency (%)
benzin 12244
62.1%
diesel 6480
32.9%
unknown 643
 
3.3%
lpg 298
 
1.5%
cng 24
 
0.1%
hybrid 16
 
0.1%
andere 7
 
< 0.1%
elektro 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
n 24386
22.5%
e 23102
21.3%
i 17168
15.8%
b 11231
10.3%
z 11212
10.3%
l 6243
 
5.8%
d 5963
 
5.5%
s 5937
 
5.5%
k 643
 
0.6%
o 643
 
0.6%
Other values (10) 2025
 
1.9%
ValueCountFrequency (%)
n 26448
22.4%
e 25222
21.4%
i 18740
15.9%
b 12260
10.4%
z 12244
10.4%
l 6780
 
5.7%
d 6503
 
5.5%
s 6480
 
5.5%
k 645
 
0.5%
o 645
 
0.5%
Other values (10) 1996
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 107911
99.4%
Uppercase Letter 642
 
0.6%
ValueCountFrequency (%)
Lowercase Letter 117320
99.5%
Uppercase Letter 643
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 24386
22.6%
e 23102
21.4%
i 17168
15.9%
b 11231
10.4%
z 11212
10.4%
l 6243
 
5.8%
d 5963
 
5.5%
s 5937
 
5.5%
k 643
 
0.6%
o 643
 
0.6%
Other values (9) 1383
 
1.3%
ValueCountFrequency (%)
n 26448
22.5%
e 25222
21.5%
i 18740
16.0%
b 12260
10.5%
z 12244
10.4%
l 6780
 
5.8%
d 6503
 
5.5%
s 6480
 
5.5%
k 645
 
0.5%
o 645
 
0.5%
Other values (9) 1353
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
U 642
100.0%
ValueCountFrequency (%)
U 643
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 108553
100.0%
ValueCountFrequency (%)
Latin 117963
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 24386
22.5%
e 23102
21.3%
i 17168
15.8%
b 11231
10.3%
z 11212
10.3%
l 6243
 
5.8%
d 5963
 
5.5%
s 5937
 
5.5%
k 643
 
0.6%
o 643
 
0.6%
Other values (10) 2025
 
1.9%
ValueCountFrequency (%)
n 26448
22.4%
e 25222
21.4%
i 18740
15.9%
b 12260
10.4%
z 12244
10.4%
l 6780
 
5.7%
d 6503
 
5.5%
s 6480
 
5.5%
k 645
 
0.5%
o 645
 
0.5%
Other values (10) 1996
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108553
100.0%
ValueCountFrequency (%)
ASCII 117963
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 24386
22.5%
e 23102
21.3%
i 17168
15.8%
b 11231
10.3%
z 11212
10.3%
l 6243
 
5.8%
d 5963
 
5.5%
s 5937
 
5.5%
k 643
 
0.6%
o 643
 
0.6%
Other values (10) 2025
 
1.9%
ValueCountFrequency (%)
n 26448
22.4%
e 25222
21.4%
i 18740
15.9%
b 12260
10.4%
z 12244
10.4%
l 6780
 
5.7%
d 6503
 
5.5%
s 6480
 
5.5%
k 645
 
0.5%
o 645
 
0.5%
Other values (10) 1996
 
1.7%

brand
Categorical

 AB Control GroupAB Test Group
Distinct4040
Distinct (%)0.2%0.2%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
volkswagen
3846 
bmw
2133 
mercedes_benz
1923 
opel
1757 
audi
1735 
Other values (35)
6758 
volkswagen
4220 
bmw
2395 
mercedes_benz
2012 
audi
1854 
opel
1844 
Other values (35)
7389 

Length

 AB Control GroupAB Test Group
Max length1414
Median length1313
Mean length6.78856326.7504312
Min length33

Characters and Unicode

 AB Control GroupAB Test Group
Total characters123226133078
Distinct characters2525
Distinct categories22 ?
Distinct scripts22 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique00 ?
Unique (%)0.0%0.0%

Sample

 AB Control GroupAB Test Group
1st rowfordopel
2nd rowbmwfiat
3rd rowhyundaivolvo
4th rowmercedes_benzford
5th rowbmwaudi

Common Values

ValueCountFrequency (%)
volkswagen 3846
21.2%
bmw 2133
11.8%
mercedes_benz 1923
10.6%
opel 1757
9.7%
audi 1735
9.6%
ford 1128
 
6.2%
renault 706
 
3.9%
peugeot 552
 
3.0%
fiat 383
 
2.1%
seat 331
 
1.8%
Other values (30) 3658
20.2%
ValueCountFrequency (%)
volkswagen 4220
21.4%
bmw 2395
12.1%
mercedes_benz 2012
10.2%
audi 1854
9.4%
opel 1844
9.4%
ford 1232
 
6.2%
renault 825
 
4.2%
peugeot 582
 
3.0%
fiat 453
 
2.3%
seat 381
 
1.9%
Other values (30) 3916
19.9%

Length

2023-04-12T16:15:18.973410image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

AB Test Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
volkswagen 3846
21.2%
bmw 2133
11.8%
mercedes_benz 1923
10.6%
opel 1757
9.7%
audi 1735
9.6%
ford 1128
 
6.2%
renault 706
 
3.9%
peugeot 552
 
3.0%
fiat 383
 
2.1%
seat 331
 
1.8%
Other values (30) 3658
20.2%
ValueCountFrequency (%)
volkswagen 4220
21.4%
bmw 2395
12.1%
mercedes_benz 2012
10.2%
audi 1854
9.4%
opel 1844
9.4%
ford 1232
 
6.2%
renault 825
 
4.2%
peugeot 582
 
3.0%
fiat 453
 
2.3%
seat 381
 
1.9%
Other values (30) 3916
19.9%

Most occurring characters

ValueCountFrequency (%)
e 16512
 
13.4%
a 10021
 
8.1%
o 9720
 
7.9%
s 8342
 
6.8%
n 8001
 
6.5%
l 6850
 
5.6%
w 6000
 
4.9%
d 5893
 
4.8%
m 5099
 
4.1%
r 4970
 
4.0%
Other values (15) 41818
33.9%
ValueCountFrequency (%)
e 17554
 
13.2%
a 10971
 
8.2%
o 10521
 
7.9%
s 8962
 
6.7%
n 8635
 
6.5%
l 7447
 
5.6%
w 6633
 
5.0%
d 6281
 
4.7%
m 5519
 
4.1%
r 5335
 
4.0%
Other values (15) 45220
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 120993
98.2%
Connector Punctuation 2233
 
1.8%
ValueCountFrequency (%)
Lowercase Letter 130750
98.3%
Connector Punctuation 2328
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 16512
13.6%
a 10021
 
8.3%
o 9720
 
8.0%
s 8342
 
6.9%
n 8001
 
6.6%
l 6850
 
5.7%
w 6000
 
5.0%
d 5893
 
4.9%
m 5099
 
4.2%
r 4970
 
4.1%
Other values (14) 39585
32.7%
ValueCountFrequency (%)
e 17554
13.4%
a 10971
 
8.4%
o 10521
 
8.0%
s 8962
 
6.9%
n 8635
 
6.6%
l 7447
 
5.7%
w 6633
 
5.1%
d 6281
 
4.8%
m 5519
 
4.2%
r 5335
 
4.1%
Other values (14) 42892
32.8%
Connector Punctuation
ValueCountFrequency (%)
_ 2233
100.0%
ValueCountFrequency (%)
_ 2328
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 120993
98.2%
Common 2233
 
1.8%
ValueCountFrequency (%)
Latin 130750
98.3%
Common 2328
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 16512
13.6%
a 10021
 
8.3%
o 9720
 
8.0%
s 8342
 
6.9%
n 8001
 
6.6%
l 6850
 
5.7%
w 6000
 
5.0%
d 5893
 
4.9%
m 5099
 
4.2%
r 4970
 
4.1%
Other values (14) 39585
32.7%
ValueCountFrequency (%)
e 17554
13.4%
a 10971
 
8.4%
o 10521
 
8.0%
s 8962
 
6.9%
n 8635
 
6.6%
l 7447
 
5.7%
w 6633
 
5.1%
d 6281
 
4.8%
m 5519
 
4.2%
r 5335
 
4.1%
Other values (14) 42892
32.8%
Common
ValueCountFrequency (%)
_ 2233
100.0%
ValueCountFrequency (%)
_ 2328
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123226
100.0%
ValueCountFrequency (%)
ASCII 133078
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 16512
 
13.4%
a 10021
 
8.1%
o 9720
 
7.9%
s 8342
 
6.8%
n 8001
 
6.5%
l 6850
 
5.6%
w 6000
 
4.9%
d 5893
 
4.8%
m 5099
 
4.1%
r 4970
 
4.0%
Other values (15) 41818
33.9%
ValueCountFrequency (%)
e 17554
 
13.2%
a 10971
 
8.2%
o 10521
 
7.9%
s 8962
 
6.7%
n 8635
 
6.5%
l 7447
 
5.6%
w 6633
 
5.0%
d 6281
 
4.7%
m 5519
 
4.1%
r 5335
 
4.0%
Other values (15) 45220
34.0%
 AB Control GroupAB Test Group
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
nein
14858 
Unknown
1887 
ja
 
1407
nein
16024 
Unknown
2209 
ja
 
1481

Length

 AB Control GroupAB Test Group
Max length77
Median length44
Mean length4.15684224.1859085
Min length22

Characters and Unicode

 AB Control GroupAB Test Group
Total characters7545582521
Distinct characters99
Distinct categories22 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique00 ?
Unique (%)0.0%0.0%

Sample

 AB Control GroupAB Test Group
1st rowUnknownnein
2nd rowneinnein
3rd rowneinja
4th rowneinUnknown
5th rowneinnein

Common Values

ValueCountFrequency (%)
nein 14858
81.9%
Unknown 1887
 
10.4%
ja 1407
 
7.8%
ValueCountFrequency (%)
nein 16024
81.3%
Unknown 2209
 
11.2%
ja 1481
 
7.5%

Length

2023-04-12T16:15:19.177955image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group

2023-04-12T16:15:19.335252image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:19.460799image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
ValueCountFrequency (%)
nein 14858
81.9%
unknown 1887
 
10.4%
ja 1407
 
7.8%
ValueCountFrequency (%)
nein 16024
81.3%
unknown 2209
 
11.2%
ja 1481
 
7.5%

Most occurring characters

ValueCountFrequency (%)
n 35377
46.9%
e 14858
19.7%
i 14858
19.7%
U 1887
 
2.5%
k 1887
 
2.5%
o 1887
 
2.5%
w 1887
 
2.5%
j 1407
 
1.9%
a 1407
 
1.9%
ValueCountFrequency (%)
n 38675
46.9%
e 16024
19.4%
i 16024
19.4%
U 2209
 
2.7%
k 2209
 
2.7%
o 2209
 
2.7%
w 2209
 
2.7%
j 1481
 
1.8%
a 1481
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 73568
97.5%
Uppercase Letter 1887
 
2.5%
ValueCountFrequency (%)
Lowercase Letter 80312
97.3%
Uppercase Letter 2209
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 35377
48.1%
e 14858
20.2%
i 14858
20.2%
k 1887
 
2.6%
o 1887
 
2.6%
w 1887
 
2.6%
j 1407
 
1.9%
a 1407
 
1.9%
ValueCountFrequency (%)
n 38675
48.2%
e 16024
20.0%
i 16024
20.0%
k 2209
 
2.8%
o 2209
 
2.8%
w 2209
 
2.8%
j 1481
 
1.8%
a 1481
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
U 1887
100.0%
ValueCountFrequency (%)
U 2209
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 75455
100.0%
ValueCountFrequency (%)
Latin 82521
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 35377
46.9%
e 14858
19.7%
i 14858
19.7%
U 1887
 
2.5%
k 1887
 
2.5%
o 1887
 
2.5%
w 1887
 
2.5%
j 1407
 
1.9%
a 1407
 
1.9%
ValueCountFrequency (%)
n 38675
46.9%
e 16024
19.4%
i 16024
19.4%
U 2209
 
2.7%
k 2209
 
2.7%
o 2209
 
2.7%
w 2209
 
2.7%
j 1481
 
1.8%
a 1481
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75455
100.0%
ValueCountFrequency (%)
ASCII 82521
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 35377
46.9%
e 14858
19.7%
i 14858
19.7%
U 1887
 
2.5%
k 1887
 
2.5%
o 1887
 
2.5%
w 1887
 
2.5%
j 1407
 
1.9%
a 1407
 
1.9%
ValueCountFrequency (%)
n 38675
46.9%
e 16024
19.4%
i 16024
19.4%
U 2209
 
2.7%
k 2209
 
2.7%
o 2209
 
2.7%
w 2209
 
2.7%
j 1481
 
1.8%
a 1481
 
1.8%

ad_created
Categorical

 AB Control GroupAB Test Group
Distinct6048
Distinct (%)0.3%0.2%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2016-03-15 0:00
 
975
2016-03-22 0:00
 
848
2016-03-21 0:00
 
825
2016-03-31 0:00
 
795
2016-04-03 0:00
 
776
Other values (55)
13933 
2016-03-20 0:00
 
1099
2016-03-09 0:00
 
910
2016-04-01 0:00
 
853
2016-04-04 0:00
 
850
2016-03-25 0:00
 
848
Other values (43)
15154 

Length

 AB Control GroupAB Test Group
Max length1515
Median length1515
Mean length1515
Min length1515

Characters and Unicode

 AB Control GroupAB Test Group
Total characters272280295710
Distinct characters1313
Distinct categories44 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique147 ?
Unique (%)0.1%< 0.1%

Sample

 AB Control GroupAB Test Group
1st row2016-03-23 0:002016-04-02 0:00
2nd row2016-03-12 0:002016-03-19 0:00
3rd row2016-03-22 0:002016-03-09 0:00
4th row2016-04-04 0:002016-03-26 0:00
5th row2016-03-22 0:002016-03-29 0:00

Common Values

ValueCountFrequency (%)
2016-03-15 0:00 975
 
5.4%
2016-03-22 0:00 848
 
4.7%
2016-03-21 0:00 825
 
4.5%
2016-03-31 0:00 795
 
4.4%
2016-04-03 0:00 776
 
4.3%
2016-03-26 0:00 763
 
4.2%
2016-03-07 0:00 737
 
4.1%
2016-03-28 0:00 731
 
4.0%
2016-03-29 0:00 677
 
3.7%
2016-03-14 0:00 670
 
3.7%
Other values (50) 10355
57.0%
ValueCountFrequency (%)
2016-03-20 0:00 1099
 
5.6%
2016-03-09 0:00 910
 
4.6%
2016-04-01 0:00 853
 
4.3%
2016-04-04 0:00 850
 
4.3%
2016-03-25 0:00 848
 
4.3%
2016-03-23 0:00 805
 
4.1%
2016-03-19 0:00 793
 
4.0%
2016-03-11 0:00 784
 
4.0%
2016-03-10 0:00 779
 
4.0%
2016-03-12 0:00 748
 
3.8%
Other values (38) 11245
57.0%

Length

2023-04-12T16:15:19.618094image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

AB Test Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
0:00 18152
50.0%
2016-03-15 975
 
2.7%
2016-03-22 848
 
2.3%
2016-03-21 825
 
2.3%
2016-03-31 795
 
2.2%
2016-04-03 776
 
2.1%
2016-03-26 763
 
2.1%
2016-03-07 737
 
2.0%
2016-03-28 731
 
2.0%
2016-03-29 677
 
1.9%
Other values (51) 11025
30.4%
ValueCountFrequency (%)
0:00 19714
50.0%
2016-03-20 1099
 
2.8%
2016-03-09 910
 
2.3%
2016-04-01 853
 
2.2%
2016-04-04 850
 
2.2%
2016-03-25 848
 
2.2%
2016-03-23 805
 
2.0%
2016-03-19 793
 
2.0%
2016-03-11 784
 
2.0%
2016-03-10 779
 
2.0%
Other values (39) 11993
30.4%

Most occurring characters

ValueCountFrequency (%)
0 97450
35.8%
- 36304
 
13.3%
2 26252
 
9.6%
1 26196
 
9.6%
6 19821
 
7.3%
3 18278
 
6.7%
18152
 
6.7%
: 18152
 
6.7%
4 4591
 
1.7%
5 2063
 
0.8%
Other values (3) 5021
 
1.8%
ValueCountFrequency (%)
0 107459
36.3%
- 39428
 
13.3%
2 28058
 
9.5%
1 27980
 
9.5%
6 21137
 
7.1%
19714
 
6.7%
: 19714
 
6.7%
3 19172
 
6.5%
4 5679
 
1.9%
9 2300
 
0.8%
Other values (3) 5069
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 199672
73.3%
Dash Punctuation 36304
 
13.3%
Space Separator 18152
 
6.7%
Other Punctuation 18152
 
6.7%
ValueCountFrequency (%)
Decimal Number 216854
73.3%
Dash Punctuation 39428
 
13.3%
Space Separator 19714
 
6.7%
Other Punctuation 19714
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 97450
48.8%
2 26252
 
13.1%
1 26196
 
13.1%
6 19821
 
9.9%
3 18278
 
9.2%
4 4591
 
2.3%
5 2063
 
1.0%
7 1861
 
0.9%
8 1593
 
0.8%
9 1567
 
0.8%
ValueCountFrequency (%)
0 107459
49.6%
2 28058
 
12.9%
1 27980
 
12.9%
6 21137
 
9.7%
3 19172
 
8.8%
4 5679
 
2.6%
9 2300
 
1.1%
7 1842
 
0.8%
5 1696
 
0.8%
8 1531
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 36304
100.0%
ValueCountFrequency (%)
- 39428
100.0%
Space Separator
ValueCountFrequency (%)
18152
100.0%
ValueCountFrequency (%)
19714
100.0%
Other Punctuation
ValueCountFrequency (%)
: 18152
100.0%
ValueCountFrequency (%)
: 19714
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 272280
100.0%
ValueCountFrequency (%)
Common 295710
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 97450
35.8%
- 36304
 
13.3%
2 26252
 
9.6%
1 26196
 
9.6%
6 19821
 
7.3%
3 18278
 
6.7%
18152
 
6.7%
: 18152
 
6.7%
4 4591
 
1.7%
5 2063
 
0.8%
Other values (3) 5021
 
1.8%
ValueCountFrequency (%)
0 107459
36.3%
- 39428
 
13.3%
2 28058
 
9.5%
1 27980
 
9.5%
6 21137
 
7.1%
19714
 
6.7%
: 19714
 
6.7%
3 19172
 
6.5%
4 5679
 
1.9%
9 2300
 
0.8%
Other values (3) 5069
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 272280
100.0%
ValueCountFrequency (%)
ASCII 295710
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 97450
35.8%
- 36304
 
13.3%
2 26252
 
9.6%
1 26196
 
9.6%
6 19821
 
7.3%
3 18278
 
6.7%
18152
 
6.7%
: 18152
 
6.7%
4 4591
 
1.7%
5 2063
 
0.8%
Other values (3) 5021
 
1.8%
ValueCountFrequency (%)
0 107459
36.3%
- 39428
 
13.3%
2 28058
 
9.5%
1 27980
 
9.5%
6 21137
 
7.1%
19714
 
6.7%
: 19714
 
6.7%
3 19172
 
6.5%
4 5679
 
1.9%
9 2300
 
0.8%
Other values (3) 5069
 
1.7%

postal_code
Real number (ℝ)

 AB Control GroupAB Test Group
Distinct54325669
Distinct (%)29.9%28.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean51737.15751749.387
 AB Control GroupAB Test Group
Minimum10671067
Maximum9999899991
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2023-04-12T16:15:19.932070image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

 AB Control GroupAB Test Group
Minimum10671067
5-th percentile10246.110249
Q13131931515
median5093451063
Q37255572379
95-th percentile9305393051
Maximum9999899991
Range9893198924
Interquartile range (IQR)4123640864

Descriptive statistics

 AB Control GroupAB Test Group
Standard deviation25715.03725603.122
Coefficient of variation (CV)0.497032280.49475217
Kurtosis-0.98206678-0.96838878
Mean51737.15751749.387
Median Absolute Deviation (MAD)2046020240
Skewness0.00115524330.0074831614
Sum9.3913288 × 1081.0201874 × 109
Variance6.6126313 × 1086.5551984 × 108
MonotonicityNot monotonicNot monotonic
2023-04-12T16:15:20.152733image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10115 47
 
0.3%
65428 29
 
0.2%
38259 21
 
0.1%
38518 21
 
0.1%
45888 19
 
0.1%
53757 18
 
0.1%
32257 18
 
0.1%
65719 18
 
0.1%
47877 17
 
0.1%
78224 17
 
0.1%
Other values (5422) 17927
98.8%
ValueCountFrequency (%)
10115 57
 
0.3%
65428 31
 
0.2%
60311 22
 
0.1%
44145 22
 
0.1%
44339 21
 
0.1%
33378 20
 
0.1%
13357 20
 
0.1%
40764 19
 
0.1%
45329 19
 
0.1%
14612 18
 
0.1%
Other values (5659) 19465
98.7%
ValueCountFrequency (%)
1067 5
< 0.1%
1068 1
 
< 0.1%
1069 2
 
< 0.1%
1097 1
 
< 0.1%
1099 5
< 0.1%
1109 2
 
< 0.1%
1127 1
 
< 0.1%
1129 2
 
< 0.1%
1139 3
< 0.1%
1156 1
 
< 0.1%
ValueCountFrequency (%)
1067 7
< 0.1%
1069 4
< 0.1%
1097 2
 
< 0.1%
1099 7
< 0.1%
1109 4
< 0.1%
1127 2
 
< 0.1%
1129 3
< 0.1%
1139 2
 
< 0.1%
1156 2
 
< 0.1%
1157 3
< 0.1%
ValueCountFrequency (%)
1067 7
< 0.1%
1069 4
< 0.1%
1097 2
 
< 0.1%
1099 7
< 0.1%
1109 4
< 0.1%
1127 2
 
< 0.1%
1129 3
< 0.1%
1139 2
 
< 0.1%
1156 2
 
< 0.1%
1157 3
< 0.1%
ValueCountFrequency (%)
1067 5
< 0.1%
1068 1
 
< 0.1%
1069 2
 
< 0.1%
1097 1
 
< 0.1%
1099 5
< 0.1%
1109 2
 
< 0.1%
1127 1
 
< 0.1%
1129 2
 
< 0.1%
1139 3
< 0.1%
1156 1
 
< 0.1%

last_seen
Categorical

 AB Control GroupAB Test Group
Distinct57656068
Distinct (%)31.8%30.8%
Missing00
Missing (%)0.0%0.0%
Memory size283.6 KiB308.0 KiB
2016-04-06 7:45
 
66
2016-04-05 23:17
 
61
2016-04-06 4:17
 
61
2016-04-06 12:17
 
60
2016-04-07 5:16
 
60
Other values (5760)
17844 
2016-04-06 17:45
 
59
2016-04-07 0:45
 
58
2016-04-06 22:16
 
58
2016-04-06 9:16
 
57
2016-04-07 7:16
 
56
Other values (6063)
19426 

Length

 AB Control GroupAB Test Group
Max length1616
Median length1616
Mean length15.60704115.630415
Min length1515

Characters and Unicode

 AB Control GroupAB Test Group
Total characters283299308138
Distinct characters1313
Distinct categories44 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 AB Control GroupAB Test Group
Unique31023115 ?
Unique (%)17.1%15.8%

Sample

 AB Control GroupAB Test Group
1st row2016-03-26 12:472016-04-06 13:17
2nd row2016-04-06 20:192016-04-07 7:15
3rd row2016-03-31 11:462016-03-16 5:46
4th row2016-04-06 12:462016-03-26 15:55
5th row2016-04-06 0:462016-03-29 14:47

Common Values

ValueCountFrequency (%)
2016-04-06 7:45 66
 
0.4%
2016-04-05 23:17 61
 
0.3%
2016-04-06 4:17 61
 
0.3%
2016-04-06 12:17 60
 
0.3%
2016-04-07 5:16 60
 
0.3%
2016-04-06 3:45 59
 
0.3%
2016-04-06 15:16 59
 
0.3%
2016-04-06 14:17 59
 
0.3%
2016-04-07 12:45 57
 
0.3%
2016-04-06 2:45 55
 
0.3%
Other values (5755) 17555
96.7%
ValueCountFrequency (%)
2016-04-06 17:45 59
 
0.3%
2016-04-07 0:45 58
 
0.3%
2016-04-06 22:16 58
 
0.3%
2016-04-06 9:16 57
 
0.3%
2016-04-07 7:16 56
 
0.3%
2016-04-05 20:45 54
 
0.3%
2016-04-06 15:46 54
 
0.3%
2016-04-06 16:17 53
 
0.3%
2016-04-06 17:16 51
 
0.3%
2016-04-06 10:17 51
 
0.3%
Other values (6058) 19163
97.2%

Length

2023-04-12T16:15:20.451894image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

AB Control Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)

AB Test Group


Number of variable categories passes threshold (config.plot.cat_freq.max_unique)
ValueCountFrequency (%)
2016-04-06 4465
 
12.3%
2016-04-07 2462
 
6.8%
2016-04-05 2145
 
5.9%
2016-03-17 525
 
1.4%
2016-03-31 487
 
1.3%
2016-04-04 480
 
1.3%
2016-04-02 475
 
1.3%
2016-04-03 450
 
1.2%
2016-03-29 426
 
1.2%
2016-03-22 407
 
1.1%
Other values (835) 23982
66.1%
ValueCountFrequency (%)
2016-04-06 4233
 
10.7%
2016-04-05 2832
 
7.2%
2016-04-07 2681
 
6.8%
2016-04-03 527
 
1.3%
2016-03-12 517
 
1.3%
2016-03-17 509
 
1.3%
2016-04-04 509
 
1.3%
2016-04-01 493
 
1.3%
2016-03-30 464
 
1.2%
2016-04-02 453
 
1.1%
Other values (846) 26210
66.5%

Most occurring characters

ValueCountFrequency (%)
0 51094
18.0%
1 40773
14.4%
- 36304
12.8%
6 29660
10.5%
2 28199
10.0%
4 24144
8.5%
18152
 
6.4%
: 18152
 
6.4%
3 12041
 
4.3%
5 9465
 
3.3%
Other values (3) 15315
 
5.4%
ValueCountFrequency (%)
0 55690
18.1%
1 44357
14.4%
- 39428
12.8%
6 31553
10.2%
2 31440
10.2%
4 25949
8.4%
19714
 
6.4%
: 19714
 
6.4%
3 13134
 
4.3%
5 10650
 
3.5%
Other values (3) 16509
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210691
74.4%
Dash Punctuation 36304
 
12.8%
Space Separator 18152
 
6.4%
Other Punctuation 18152
 
6.4%
ValueCountFrequency (%)
Decimal Number 229282
74.4%
Dash Punctuation 39428
 
12.8%
Space Separator 19714
 
6.4%
Other Punctuation 19714
 
6.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51094
24.3%
1 40773
19.4%
6 29660
14.1%
2 28199
13.4%
4 24144
11.5%
3 12041
 
5.7%
5 9465
 
4.5%
7 8620
 
4.1%
8 3702
 
1.8%
9 2993
 
1.4%
ValueCountFrequency (%)
0 55690
24.3%
1 44357
19.3%
6 31553
13.8%
2 31440
13.7%
4 25949
11.3%
3 13134
 
5.7%
5 10650
 
4.6%
7 9355
 
4.1%
8 3909
 
1.7%
9 3245
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 36304
100.0%
ValueCountFrequency (%)
- 39428
100.0%
Space Separator
ValueCountFrequency (%)
18152
100.0%
ValueCountFrequency (%)
19714
100.0%
Other Punctuation
ValueCountFrequency (%)
: 18152
100.0%
ValueCountFrequency (%)
: 19714
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 283299
100.0%
ValueCountFrequency (%)
Common 308138
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 51094
18.0%
1 40773
14.4%
- 36304
12.8%
6 29660
10.5%
2 28199
10.0%
4 24144
8.5%
18152
 
6.4%
: 18152
 
6.4%
3 12041
 
4.3%
5 9465
 
3.3%
Other values (3) 15315
 
5.4%
ValueCountFrequency (%)
0 55690
18.1%
1 44357
14.4%
- 39428
12.8%
6 31553
10.2%
2 31440
10.2%
4 25949
8.4%
19714
 
6.4%
: 19714
 
6.4%
3 13134
 
4.3%
5 10650
 
3.5%
Other values (3) 16509
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 283299
100.0%
ValueCountFrequency (%)
ASCII 308138
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51094
18.0%
1 40773
14.4%
- 36304
12.8%
6 29660
10.5%
2 28199
10.0%
4 24144
8.5%
18152
 
6.4%
: 18152
 
6.4%
3 12041
 
4.3%
5 9465
 
3.3%
Other values (3) 15315
 
5.4%
ValueCountFrequency (%)
0 55690
18.1%
1 44357
14.4%
- 39428
12.8%
6 31553
10.2%
2 31440
10.2%
4 25949
8.4%
19714
 
6.4%
: 19714
 
6.4%
3 13134
 
4.3%
5 10650
 
3.5%
Other values (3) 16509
 
5.4%

Interactions

AB Control Group

2023-04-12T16:14:59.875679image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:10.664869image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.105369image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:04.373733image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.966717image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:05.454604image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.851559image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:06.509785image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:56.876987image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:07.614065image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:57.863487image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:08.722326image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.864969image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:09.725994image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:15:00.005207image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:10.782599image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.218258image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:04.483579image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.105787image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:05.626124image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.985178image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:06.611881image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:56.986736image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:07.752370image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.017623image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:08.815853image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.972896image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:09.853218image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:15:00.154626image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:10.945649image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.334799image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:04.660596image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.234140image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:05.778996image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:56.118873image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:06.749980image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:57.150225image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:07.910252image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.163891image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:08.961874image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:59.092276image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:09.997223image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:15:00.242321image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:11.082898image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.458241image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:04.776743image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.360037image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:05.928542image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:56.254384image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:06.845324image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:57.294430image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:08.099966image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.271050image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:09.112106image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:59.354125image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:10.142110image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:15:00.408707image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:11.228207image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.608681image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:04.944387image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.460134image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:06.082863image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:56.368118image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:07.027789image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:57.419762image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:08.328347image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.435419image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:09.257908image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:59.477207image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:10.286629image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:15:00.571000image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:11.351638image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.702096image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:05.075502image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.616540image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:06.193681image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:56.548150image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:07.218288image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:57.604839image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:08.467934image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.608366image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:09.414261image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:59.603394image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:10.444316image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:15:00.712303image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:11.493716image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:54.818318image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:05.344692image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:55.720152image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:06.347210image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:56.742708image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:07.447711image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:57.720181image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:08.596016image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:58.751537image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:09.590484image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Control Group

2023-04-12T16:14:59.739508image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:10.576194image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

AB Control Group

2023-04-12T16:15:20.609454image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:20.813559image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:
  • Variable_type-Variable_type : Method, Range
  • Categorical-Categorical : Cramer's V, [0,1]
  • Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
  • Numerical-Numerical : Spearman's ρ, [-1,1]
The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.

AB Control Group

2023-04-12T16:15:21.017669image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:21.174840image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

AB Control Group

2023-04-12T16:15:21.348425image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:21.663416image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

AB Control Group

2023-04-12T16:15:21.836160image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:22.024819image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

AB Control Group

2023-04-12T16:15:22.203513image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:22.338598image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

AB Control Group

2023-04-12T16:15:22.495398image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

AB Test Group

2023-04-12T16:15:22.683970image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

AB Control Group

2023-04-12T16:15:00.954452image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.

AB Test Group

2023-04-12T16:15:11.875892image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.

AB Control Group

2023-04-12T16:15:01.354793image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

AB Test Group

2023-04-12T16:15:12.333923image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AB Control Group

Unnamed: 0date_crawledcar_nameprice_EURab_testvehicle_typeregistration_yeartransmissionpower_psmodelodometer_kmregistration_monthfuel_typebrandunrepaired_damagead_createdpostal_codelast_seen
562016-03-23 19:43Ford_Mondeo_V6_170_PS550controllimousine1999automatik170mondeo1500006benzinfordUnknown2016-03-23 0:00254512016-03-26 12:47
672016-03-12 13:46BMW_320d_DPF_Touring10400controlkombi2008manuell1773er1250005dieselbmwnein2016-03-12 0:00941072016-04-06 20:19
10152016-03-22 14:50Hyundai_i30_1.6_CRDi_Edition_207990controllimousine2012manuell90i_reihe600006dieselhyundainein2016-03-22 0:00667012016-03-31 11:46
11162016-04-04 11:50Mercedes_Benz_E_320_T_CDI_Avantgarde__Vollausstattung3800controlkombi2000automatik197e_klasse1500002dieselmercedes_benznein2016-04-04 0:00498322016-04-06 12:46
12182016-03-22 11:59BMW_120d_DPF_Bus._Navi__Harman&Kardon__Schiebedach13999controllimousine2010manuell1771er7000012dieselbmwnein2016-03-22 0:00912202016-04-06 0:46
13202016-03-17 17:42Ford_Streetka_1.6l___95_PS1350controlcabrio2004manuell95ka1500007benzinfordUnknown2016-03-17 0:00254362016-03-17 17:42
14212016-03-08 0:53Audi_TT_Coupe_1.8_T3250controlcoupe1999manuell179tt1500004benzinaudinein2016-03-08 0:00705992016-04-05 23:44
15222016-03-29 19:51Bmw_525..panoramadach..voll_leder.Tausch_moglich_mit_7_sitzer.6950controlkombi2006automatik177Unknown1500006dieselbmwnein2016-03-29 0:00494972016-04-06 6:15
16252016-03-21 14:39Volkswagen_Golf_Plus_1.4_Comfortline3750controlbus2005manuell75golf1500005benzinvolkswagennein2016-03-21 0:00441492016-03-21 14:39
17302016-03-21 12:50VOLVO_V70_!!!_2_5_Liter_5_Zylinder_TÜV_bis_01/2018__8fach_bereift2100controlkombi1998manuell144v7015000010benzinvolvonein2016-03-21 0:00326832016-04-06 7:45

AB Test Group

Unnamed: 0date_crawledcar_nameprice_EURab_testvehicle_typeregistration_yeartransmissionpower_psmodelodometer_kmregistration_monthfuel_typebrandunrepaired_damagead_createdpostal_codelast_seen
012016-04-02 14:51Astra_G_Cabrio_Turbo_235_PS5200testcabrio2002manuell235astra1250005Unknownopelnein2016-04-02 0:00476522016-04-06 13:17
122016-03-19 18:36Fiat_Grande_Punto_1.2_8V__MIT_2_JAHREN_GARANTIE3400testkleinwagen2006manuell65andere1250005benzinfiatnein2016-03-19 0:00665382016-04-07 7:15
232016-03-09 20:59Volvo_XC60_D5_AWD_Aut.5200testsuv2009automatik220xc_reihe1500003dieselvolvoja2016-03-09 0:00727622016-03-16 5:46
342016-03-26 15:55Kombi_Technisch_super_in_Schuss750testkombi2000manuell112mondeo15000012benzinfordUnknown2016-03-26 0:00394462016-03-26 15:55
452016-03-29 14:47Audi_A4_1.9_TDI_quattro_Delphingrau3522testlimousine2004manuell131a41500007dieselaudinein2016-03-29 0:00513732016-03-29 14:47
7122016-03-30 18:37BMW_318i_dunkelblau2499testkombi2000manuell1183er1500001benzinbmwnein2016-03-30 0:0044632016-04-03 8:47
8132016-03-26 2:57Cadillac_CTS_3.6_V6_Sport_Wagon_AWD___SPORT__LUXURY14500testkombi2011automatik311Unknown1500007benzinsonstige_autosnein2016-03-26 0:00223052016-04-05 19:47
9142016-03-22 1:49VW_passat2100testlimousine1998manuell101passat1500001benzinvolkswagennein2016-03-21 0:00182732016-03-29 7:16
18332016-03-30 13:57Renault__Mit_Scheckheft_org.86_Tkm1699testkleinwagen2002manuell75twingo900005benzinrenaultnein2016-03-30 0:00245392016-04-07 5:15
19352016-03-11 23:53Ford_Galaxy_16V_GLX999testbus1998manuell145galaxy15000010benzinfordnein2016-03-11 0:00852902016-03-18 0:44

AB Control Group

Unnamed: 0date_crawledcar_nameprice_EURab_testvehicle_typeregistration_yeartransmissionpower_psmodelodometer_kmregistration_monthfuel_typebrandunrepaired_damagead_createdpostal_codelast_seen
37845499732016-03-25 14:52Opel_Corsa_1.2_16V_ecoFLEX_Easytroni_Color_Stripes4199controlkleinwagen2011Unknown86corsa15000010benzinopelnein2016-03-25 0:00135892016-03-28 14:18
37846499742016-03-30 9:54BMW_316_mit_TÜV_bis_Mai_2017_Top_Zustand..1600controllimousine1996manuell1023er1500006benzinbmwUnknown2016-03-30 0:0010672016-04-07 0:17
37848499762016-03-12 9:48Smart_CDI_Gruene_Plakette_TÜV_NEU_!!!1799controlcoupe2000automatik41fortwo15000012dieselsmartnein2016-03-12 0:00415162016-03-14 17:45
37853499832016-03-17 13:51Opel_Astra_2.2_16V_Coupe3300controlcoupe2000manuell147astra1500008benzinopelnein2016-03-17 0:00593682016-04-06 20:17
37855499852016-04-04 10:53Mercedes_Benz_A_150_Classic_/_Klima_/_Scheckheft_/_AHK5600controllimousine2007manuell95a_klasse12500011benzinmercedes_benznein2016-04-04 0:00442272016-04-06 12:17
37857499872016-04-01 18:49Verkaufe_Renault_Laguna_3_Grandtour_mit_Frontschaden4950controlkombi2008manuell110laguna1250009dieselrenaultja2016-04-01 0:00374412016-04-01 18:49
37860499932016-03-21 16:51BMW_316i_compact1200controllimousine1997manuell1023er1500007benzinbmwja2016-03-21 0:00542932016-04-06 16:45
37862499952016-03-10 0:59Toyota_RAV_4_2.2D_110_kw6590controlsuv2010manuell150rav1500006dieseltoyotanein2016-03-09 0:00668712016-03-10 8:42
37863499962016-03-06 17:46Mercedes_190e_W2011250controllimousine1991manuell120c_klasse1500001benzinmercedes_benznein2016-03-06 0:00255602016-04-06 6:16
37865499982016-03-13 8:47FIAT_PUNTO_1.2___16V__SPORTING___TÜV_neu__999controlkleinwagen1998manuell85punto1500001benzinfiatnein2016-03-13 0:00248572016-03-14 9:45

AB Test Group

Unnamed: 0date_crawledcar_nameprice_EURab_testvehicle_typeregistration_yeartransmissionpower_psmodelodometer_kmregistration_monthfuel_typebrandunrepaired_damagead_createdpostal_codelast_seen
37849499792016-04-01 17:44Audi_Cabriolet_1.83750testcabrio1998manuell125andere1500005benzinaudinein2016-04-01 0:00907662016-04-05 12:47
37850499802016-03-28 16:38Mercedes_Benz_CLA_250_7G_DCT_AMG_Line34750testcoupe2013automatik211andere300008benzinmercedes_benznein2016-03-28 0:00676592016-04-06 21:44
37851499812016-03-09 21:50Audi_A6_2.411990testlimousine2007manuell177a6300005benzinaudinein2016-03-09 0:00383502016-03-17 6:16
37852499822016-03-28 16:51Volkswagen_Multivan_DSG_Startline25900testbus2012automatik140transporter1250003dieselvolkswagennein2016-03-28 0:00364482016-03-30 8:16
37854499842016-03-27 7:57Mercedes_Benz_E280_CDI7000testlimousine2004automatik177e_klasse1500008dieselmercedes_benzUnknown2016-03-27 0:00683092016-04-07 5:17
37856499862016-04-03 15:36Audi_A3_1.6_Attraction4750testlimousine2004manuell102a31500004benzinaudinein2016-04-03 0:00521522016-04-05 14:44
37858499882016-03-09 16:55Mercedes_Benz_G_290_Offroad_Ausbau26500testsuv1996manuell95g_klasse1500009dieselmercedes_benznein2016-03-09 0:00737332016-04-07 6:45
37859499912016-03-30 18:43Audi_A3_1.6_Liter_TOP!4650testlimousine2004manuell150a31500003benzinaudinein2016-03-30 0:00582562016-04-07 9:45
37861499942016-03-13 12:41Mercedes_Benz_Vaneo_CDI_1.7_Family3000testbus2002manuell91andere1500003dieselmercedes_benznein2016-03-13 0:00962682016-04-06 15:17
37864499972016-03-09 0:56Peugeot_Boxer_HDi_335_L2H2_verglast12500testbus2011manuell120andere1250006dieselpeugeotnein2016-03-09 0:00691232016-03-11 12:17

Duplicate rows

AB Control Group

Unnamed: 0date_crawledcar_nameprice_EURab_testvehicle_typeregistration_yeartransmissionpower_psmodelodometer_kmregistration_monthfuel_typebrandunrepaired_damagead_createdpostal_codelast_seen# duplicates
Dataset does not contain duplicate rows.

AB Test Group

Unnamed: 0date_crawledcar_nameprice_EURab_testvehicle_typeregistration_yeartransmissionpower_psmodelodometer_kmregistration_monthfuel_typebrandunrepaired_damagead_createdpostal_codelast_seen# duplicates
Dataset does not contain duplicate rows.